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  <p>大模型中心开展大模型系统架构、学习算法和领域应用的创新研究，为新一代人工智能提供核心技术。主要研究方向包括：面向大模型的可扩展系统架构、面向大模型的高效能机器学习算法与平台、大模型知识增强学习算法，以及语言大模型、多模态大模型、科学大模型、具身决策大模型、智能体系统，以及神经符号推理系统等。</p>
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        大语言模型：人工智能语言理解与生成的新纪元 大语言模型（Large Language Models, LLMs） 是近年来人工智能领域最具突破性的技术之一。它们通过海量数据训练，能够理解和生成自然语言，在文本生成、翻译、问答等任务中展现出接近人类水平的能力，开启了人工智能语言理解与生成的新纪元。
核心技术突破 大语言模型的成功得益于以下关键技术的突破：
总而言之，大语言模型正在深刻改变我们与机器的交互方式，并为各行各业带来前所未有的机遇。 随着技术的不断进步和应用场景的不断拓展，它们将继续推动人工智能语言理解与生成领域的发展，为人类社会创造更多价值。</a></p>
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        南京大学大模型知识增强研究小组长期从事大模型知识增强、大模型可控生成、领域大模型构建等方向研究。</a></p>
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        大模型机器学习算法与平台研究小组致力于探索高效能训练和推理机器学习算法，并构建相应的平台与系统，支撑大模型的高准确率、低成本训练和部署。</a></p>
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        大模型软件与系统研究小组致力于探索大模型与软件、系统之间的双向互动关系。一方面，我们研究如何利用大模型来优化和改进软件与系统的设计、开发、测试、验证与运维；另一方面，我们也关注如何设计和构建高效的软件与系统来支持大模型的训练、推理和部署。通过这两个方向的深度融合，我们旨在推动大模型与软件、系统的协同创新，为人工智能驱动的未来计算生态提供技术支撑。</a></p>
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